Applied Statistics for Life Sciences

Updated

May 19, 2025

Statistics plays a crucial role in the sciences: statistical techniques provide a means of weighing quantitative evidence derived from observation and experimentation while accounting for uncertainty. This class aims to provide a hands-on introduction to common statistical methods used almost universally across the sciences and a primer on statistical concepts. Examples from the life sciences emphasize applications with relevance to students’ majors, and students learn to perform simple analyses in R.

Read the [course syllabus] for more information.

Announcements
  • Test 2 corrections due in class Tuesday 5/20/25
  • HW9 due 11:59pm PDT Tuesday 5/20/25
  • Test 3 due 11:59pm PDT Friday 5/23/25

Instructor: Trevor Ruiz (he/him) [email]

Learning assistant: Emi Degembe (she/they) [email]

Class meetings:

Office hours and learning assistant hours:

Preparing for class meetings:

  1. Complete any outstanding problems or other work from prior class meetings; these should be submitted by the start of class.
  2. Check the course website for posted reading and materials. Readings should be skimmed in advance of class meetings and read in depth after class meetings.

Week 1 (3/31/25)

Tuesday: study design and data semantics

  • [reading] Vu and Harrington 1.1 - 1.3
  • [lecture] course intro; study designs and data semantics
  • [lab] R basics [solutions]

Thursday: descriptive statistics

Week 2 (4/7/25)

Tuesday: point estimation

  • [reading] Vu and Harrington 4.1
  • [lecture] point estimation and sampling variability
  • [lab] point and interval estimation for a population mean [solutions]
  • [HW2] due next class [prompts] [submit] [solutions]

Thursday: interval estimation

  • [reading] Vu and Harrington 3.3.1, 3.3.2, and 3.3.3; and 4.2
  • [lecture] confidence interval coverage and critical values
  • [lab] computing critical values [solutions]
  • [HW3] due next class [prompts] [submit] [solutions]

Week 3 (4/14/25)

Tuesday: one-sample inference for a population mean

  • [reading] Vu and Harrington 4.3.1-4.3.4
  • [lecture] intro to hypothesis testing
  • [lab] one-sample t-tests in R [solutions]
  • [HW4] finish lab activity by next class [submit]

Thursday: test 1 review

Week 4 (4/21/25)

Tuesday: two-sample inference for a difference in population means

Thursday: analysis of variance (ANOVA)

  • [reading] Vu and Harrington 5.5.1 & 5.5.2
  • [lecture] statistical power; intro to analysis of variance
  • [lab] fitting ANOVA models in R [solutions]
  • [HW6] due next class [prompts] [submit]

Week 5 (4/28/25)

Tuesday: post-hoc inference in ANOVA

  • [reading] Vu and Harrington 5.5.3 & 5.5.4
  • [lecture] post hoc inference in ANOVA
  • [lab] pairwise comparisons and contrasts using emmeans in R [solutions]
  • [HW6] due Tuesday 5/6/25 [prompts] [submit] [solutions]

Thursday: test 2 review

Week 6 (5/5/25)

Tuesday: test 2

Thursday: nonparametric inference

  • [reading] van Belle et al. 8.4 and 8.5 up to 8.5.4
  • [lecture] nonparametric alternatives to t tests and F tests
  • [lab] nonparametric inference in R [solutions]
  • [HW7] due next class [prompts] [submit] [solutions]

Week 7 (5/12/25)

Tuesday: simple linear regression

  • [reading] Vu and Harrington 6.1 & 6.2
  • [lecture] least squares estimation
  • [lab] line fitting activity [solutions]
  • [HW8] due next class [prompts] [submit]

Thursday: inference in regression

  • [reading] Vu and Harrington 6.4 & 6.5
  • [lecture] inference for SLR
  • [lab] fitting SLR models; predictions [solutions]
  • [HW9] due next class [prompts] [submit]

Week 8 (5/19/25)

Tuesday: inference for proportions

  • [reading] Vu and Harrington 8.1 & 8.2
  • [lecture] inference for population proportions
  • [lab] inference for proportions in R
  • [HW10] due next class [prompts] [submit]

Thursday: analysis of contingency tables

  • [reading] Vu and Harrington 8.3
  • [lecture] tests of association in two-way tables
  • [lab] χ2 tests in R
  • [HW11] due Thursday 5/29/25

Friday: test 3 due 11:59pm PDT 5/23/25

Week 9 (5/26/25)

Memorial Day observed – no classes Monday and Tuesday follows a Monday schedule.

Tuesday: no class meeting

Thursday: goodness of fit tests

  • [reading] Vu and Harrington 8.4

Week 10 (6/2/24)

Tuesday: inference for relative risk and odds ratios

  • [reading] Vu and Harrington 8.5

Thursday: review for final

Exam info

Scheduled tests:

  • Test 1: take home due Friday 4/18/25
  • Test 2: in class Tuesday 5/6/25
  • Test 3: take home due Friday 5/23/25
  • Final: common final Saturday 6/7/25 1:10pm–4:00pm 26-104

Resources: